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BackgroundCases of large-cell neuroendocrine carcinoma (NEC) concomitant hepatocellular carcinoma (HCC) are very rare. Based on the microscopic characteristics, mixed HCC-NEC tumors can be divided into collision type and combined type. We report a patient with both collision and combined type HCC-NEC tumor at the same time.Case presentationA 58-year-old man with hepatitis B and cirrhosis was found to have two masses in segment 5 and segment 8 of the liver, respectively. Preoperative imaging diagnosis was primary liver cancer. Indocyanine green retention test (ICG R15)

BackgroundAdult secondary hemophagocytic lymphohistiocytosis (sHLH) is a rare clinical syndrome with a high mortality rate. Currently, there are no feasible prognostic factors to clinically predict untreated sHLH patients’ prognosis. Our objective was to characterize the lipid profile of adult sHLH patients and to determine the relationship with overall survival.MethodsWe retrospectively analyzed 247 patients with newly diagnosed sHLH from January 2017 to January 2022 according to the HLH-2004 criteria. Multivariate Cox regression analyses and restricted cubic splines were conducted to evaluate the prognostic value of the lipid profile.ResultsThe median age of all patients was 52 years, and the commonest cause of sHLH in our cohort was malignancy. During a median follow-up of 88 (interquartile ranges, 22–490) days, 154 deaths occurred. The univariate analysis confirmed total cholesterol (TC) ≤ 3 mmol/L, triglycerides (TG) > 3.08 mmol/L, high-density lipoprotein cholesterol (HDL-c) ≤ 0.52 mmol/L, and low-density lipoprotein cholesterol (LDL-c) ≤ 2.17 mmol/L were associated with an inferior survival. In a multivariate model, HDL-c, hemoglobin, platelet, fibrinogen, and soluble interleukin-2 receptor were considered as independent factors. Additionally, the restricted cubic spline analyses indicated an inverse linear association between HDL-c and the risk of mortality in sHLH.ConclusionLipid profiles, which were low-cost and readily available promising biomarkers, were strongly associated with the overall survival in adult sHLH patients.

PurposeSpinal metastasis of malignant adrenal tumor (SMMAT) is an extremely rare and poorly understood malignant tumor originating from the adrenal gland. The objective of this study is to elucidate the clinical characteristics and discuss surgical management and outcomes of SMMAT.MethodsIncluded in this study were six SMMAT patients who received surgical treatment in our center between February 2013 and May 2022. Their clinical data and outcomes were retrospectively analyzed to gain a better understanding of SMMAT. In addition, ten cases from the literature focusing on SMMAT were also reviewed.ResultsSurgery was performed successfully, and the associated symptoms were relieved significantly in all patients postoperatively. The mean follow-up duration was 26.2 (range 3-55) months. Two patients died of tumor recurrence 12 and 48 months after operation respectively. The other four patients were alive at the last follow-up.ConclusionsThe prognosis of SMMAT is usually poor. Preoperative embolization and early surgical radical resection can offer satisfactory clinical outcomes. The patient’s health status, preoperative neurological function, tumor location and the resection mode are potential prognostic factors of SMMAT.

Extra-neural spread of glioblastoma (GBM) is extremely rare. We report a case of postoperative intracranial GBM spreading to the subcutaneous tissue via the channel of craniotomy defect in a 73-year-old woman. Radiological images and histopathology indicate that the tumor microenvironment of the subcutaneous tumor is clearly different from the intracranial tumor. We also model the invasion of GBM cells through the dura-skull defect in mouse. The retrospective analysis of GBM with scalp metastases suggests that craniectomy is a direct cause of subcutaneous metastasis in patients with GBM. Imaging examinations of other sites for systemic screening is also recommended to look for metastases outside the brain when GBM invades the scalp or metastasizes to it.

PurposeTo establish a predictive model to predict the occurrence of language deficit for patients after surgery of glioma involving language areas (GILAs) under general anesthesia (GA).MethodsPatients with GILAs were retrospectively collected in our center between January 2009 and December 2020. Clinical variables (age, sex, aphasia quotient [AQ], seizures and KPS), tumor-related variables (recurrent tumor or not, volume, language cortices invaded or not, shortest distance to language areas [SDLA], supplementary motor area or premotor area [SMA/PMA] involved or not and WHO grade) and intraoperative multimodal techniques (used or not) were analyzed by univariate and multivariate analysis to identify their association with temporary or permanent language deficits (TLD/PLD). The predictive model was established according to the identified significant variables. Receiver operating characteristic (ROC) curve was used to assess the accuracy of the predictive model.ResultsAmong 530 patients with GILAs, 498 patients and 441 patients were eligible to assess TLD and PLD respectively. The multimodal group had the higher EOR and rate of GTR than conventional group. The incidence of PLD was 13.4% in multimodal group, which was much lower than that (27.6%, P

BackgroundCancer-associated fibroblasts (CAFs) are vital components of prominent cellular components in lower-grade gliomas (LGGs) that contribute to LGGs’ progression, treatment resistance, and immunosuppression. Epigenetic modification and immunity have significant implications for tumorigenesis and development.MethodsWe combined aberrant methylation and CAFs abundances to build a prognostic model and the impact on the biological properties of LGGs. Grouping based on the median CAFs abundances score of samples in the TCGA-LGGs dataset, differentially expressed genes and aberrantly methylated genes were combined for subsequent analysis.ResultsWe identified five differentially methylated and expressed genes (LAT32, SWAP70, GSAP, EMP3, and SLC2A10) and established a prognostic gene signature validated in the CGGA-LGGs dataset. Immunohistochemistry (IHC) and in vitro tests were performed to verify these expressions. The high-risk group increased in tumor-promoting immune cells and tumor mutational burden. Notably, risk stratification had different ICB sensitivities in LGGs, and there were also significant sensitivity differences for temozolomide and the other three novel chemotherapeutic agents.ConclusionOur study reveals characteristics of CAFs in LGGs, refines the direct link between epigenetics and tumor stroma, and might provide clinical implications for guiding tailored anti-CAFs therapy in combination with immunotherapy for LGGs patients.

PurposePatients with lung cancer with bone metastasis (LCBM) often have a very poor prognosis. The purpose of this study is to characterize the prevalence and associated factors and to develop a prognostic nomogram to predict the overall survival (OS) and cancer-specific survival (CSS) for patients with LCBM using multicenter population-based data.MethodsPatients with LCBM at the time of diagnosis were identified using the Surveillance, Epidemiology, and End Results (SEER) Program database of the National Cancer Institute (NCI) from 2010 to 2015. Multivariable and univariate logistic regression analyses were performed to identify factors associated with all-cause mortality and lung cancer (LC)–specific mortality. The performance of the nomograms was evaluated with the calibration curves, area under the curve (AUC), and decision curve analysis (DCA). Kaplan–Meier analysis and log-rank tests were used to estimate the survival times of patients with LCBM.ResultsWe finally identified 26,367 patients with LCBM who were selected for survival analysis. Multivariate analysis demonstrated age, sex, T stage, N stage, grade, histology, radiation therapy, chemotherapy, primary site, primary surgery, liver metastasis, and brain metastasis as independent predictors for LCBM. The AUC values of the nomogram for the OS prediction were 0.755, 0.746, and 0.775 in the training cohort; 0.757, 0.763, and 0.765 in the internal validation cohort; and 0.769, 0.781, and 0.867 in the external validation cohort. For CSS, the values were 0.753, 0.753, and 0.757 in the training cohort; 0.753, 0.753, and 0.757 in the internal validation cohort; and 0.767, 0.774, and 0.872 in the external validation cohort.ConclusionsOur study constructs a new prognostic model and clearly presents the clinicopathological features and survival analysis of patients with LCBM. The result indicated that the nomograms had favorable discrimination, good consistency, and clinical benefits in patients. In addition, our constructed nomogram prediction models may assist physicians in evaluating individualized prognosis and deciding on treatment for patients.

PurposeWe hypothesized that posterior quadratus lumborum block would reduce postoperative opioid consumption and improve the quality of recovery in patients undergoing sutureless laparoscopic partial nephrectomy.Materials and methodsThe study included 60 patients, ages 18−65 with American Society of Anesthesiologists scores of I-II scheduled for elective sutureless laparoscopic partial nephrectomy. Before general anesthesia, 60 participating patients were randomly allocated to receive a 30-ml injection posterior to the quadratus lumborum muscle with either 0.375% ropivacaine (n = 30) or normal saline (n = 30). The primary outcomes included cumulative opioid consumption within 12 h postoperatively and quality of postoperative recovery at 48 h. Secondary outcomes included the Numerical Rating Scale (NRS), opioid consumption by period, first time to press the analgesic pump, number of patients needing rescue analgesia, blood glucose and cortisol concentrations, early postoperative recovery indicators, and adverse events.ResultsThere were 48 patients included in the final analysis. The intervention group had lower cumulative consumption of sufentanil within 12 h postoperatively and higher quality of postoperative recovery scores at 48 h postoperatively compared with the control group (p < 0.001). The NRS at resting and movement of the intervention group was lower at 0 h, 6 h, and 12 h after surgery than in the control group (p < 0.05). At prespecified intervals (0 to 2 h, 2 to 6 h, 6 to 12 h, 12 to 24 h, and 24 to 48 h) after surgery, the intervention group had lower consumption of sufentanil compared with the control group (p < 0.05). The intervention group took longer to press the analgesic pump for the first time within 48 h after surgery compared with the control group (p < 0.001). The postoperative blood glucose and cortisol concentrations in the intervention group were lower than in the control group (p < 0.05). The times to first excretion, ambulation, and discharge were shorter in the intervention group compared with the control group (p < 0.05). There was no significant difference in adverse events between the two groups.ConclusionsOur trial demonstrated that patients who received posterior quadratus lumborum block had significantly lower opioid consumption within 12 h postoperatively and had a better quality of recovery at 48 h postoperatively. Therefore, we recommend posterior quadratus lumborum block as an option for postoperative analgesia in patients undergoing sutureless laparoscopic partial nephrectomy.Trial Registrationhttp://www.chictr.org.cn, identifier ChiCTR2100053439.

CircRNAs have been the focus of research in recent years. They are differentially expressed in various human tumors and can regulate oncogenes and tumor suppressor genes expression through various mechanisms. The diversity, stability, evolutionary conservatism and cell- or tissue-specific expression patterns of circRNAs also endow them with important regulatory roles in promoting or inhibiting tumor cells malignant biological behaviors progression. More interestingly, emerging studies also found that circRNAs can regulate not only other genes expression, but also their parental gene expression and thus influence tumors development. Apart from some conventional features, circRNAs have a certain specificity in the regulation of parental gene expression, with a higher proportion affecting parental gene transcription and easier translation into protein to regulate parental gene expression. CircRNAs are generally thought to be unable to produce proteins and therefore the protein-coding ability exhibited by circRNAs in regulating parental gene expression is unique and indicates that the regulatory effects of parental gene expression by circRNAs are not only a competitive binding relationship, but also a more complex molecular relationship between circRNAs and parental gene, which deserves further study. This review summarizes the molecular mechanisms of circRNAs regulating parental gene expression and their biological roles in tumorigenesis and development, aiming to provide new ideas for the clinical application of circRNAs in tumor-targeted therapy.

Exosomes are lipid membrane bilayer-encapsulated vesicles secreted by cells into the extracellular space. They carry abundant inclusions (such as nucleic acids, proteins, and lipids) that play pivotal roles in intercellular communication. Tumor stem cells are capable of self-renewal and are crucial for survival, proliferation, drug resistance, metastasis, and recurrence of tumors. The miRNAs (microRNAs) in exosomes have various functions, such as participating in inflammatory response, cell migration, proliferation, apoptosis, autophagy, and epithelial-mesenchymal transition. Tumor stem cells secrete exosomes that act as important messengers involved in various tumor processes and several studies provide increasing evidence supporting the importance of these exosomes in tumor recurrence and metastasis. This review primarily focuses on the production and secretion of exosomes from tumors and tumor stem cells and their effects on cancer progression. Cancer stem cancer derived exosome play an important massager in the tumor microenvironment. It also emphasizes on the study of tumor stem cell exosomes in the light of cancer metastasis and recurrence aiming to provide valuable insights and novel perspectives, which could be beneficial for developing effective diagnostic and treatment strategies.

BackgroundThis study determined the predictive value of CRMP4 promoter methylation in prostate tissues collected by core needle biopsies for a postoperative upgrade of Gleason Score (GS) to ≥8 in patients with low-risk PCa.MethodA retrospective analysis of the clinical data was conducted from 631 patients diagnosed with low-risk PCa by core needle biopsy at multiple centers and then underwent Radical Prostatectomy (RP) from 2014-2019. Specimens were collected by core needle biopsy to detect CRMP4 promoter methylation. The pathologic factors correlated with the postoperative GS upgrade to ≥8 were analyzed by logistic regression. The cut-off value for CRMP4 promoter methylation in the prostate tissues collected by core needle biopsy was estimated from the ROC curve in patients with a postoperative GS upgrade to ≥8.ResultMultivariate logistic regression showed that prostate volume, number of positive cores, and CRMP4 promoter methylation were predictive factors for a GS upgrade to ≥8 (OR: 0.94, 95% CI: 0.91-0.98, P=0.003; OR: 3.16, 95% CI: 1.81-5.53, P18.00%, the low-risk PCa patients were more likely to escalate to high-risk patients. The predictive sensitivity and specificity were 86.9% and 98.8%, respectively. The area under the ROC curve (AUC) was 0.929 (95% CI: 0.883-0.976; P18.0% and postoperative GS upgrade to ≥8 than in patients without an upgrade (P ≤ 0.002).ConclusionA CRMP4 promoter methylation rate >18.00% in prostate cancer tissues indicated that patients were more likely to escalate from low-to-high risk after undergoing an RP. We recommend determining CRMP4 promoter methylation before RP for low-risk PCa patients.

ObjectiveAccumulating evidence has highlighted the roles of long noncoding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) of microRNAs (miRNAs) through their binding sites in the progression of glioma. Hereby, we aim to explore the role of LINC00883 as a regulator of miR-136 and its target, NIMA-related kinase 1 (NEK1), thus, its involvement in the drug resistance of glioma cells.Methods and ResultsMechanistic investigations by dual-luciferase reporter, RNA pull-down, and RNA-binding protein immunoprecipitation (RIP) assays indicated that LINC00883 bound to miR-136, thereby blocking miR-136-induced downregulation of NEK1. Through gain-of-function experiments in U251 cells that presented a high drug resistance, we found that ectopic expression of LINC00883 resulted in increased MRP (encoding multidrug resistance-associated protein), limited cell apoptosis, and increased proliferation. Expectedly, depleting LINC00883 yielded tumor-suppressive and anti-chemoresistance effects on U251 cells by increasing miR-136 and inhibiting NEK1. Next, drug-resistant glioma cell line SOWZ1, drug-sensitive glioma cell line SOWZ2, and drug-resistant glioma cell line SOWZ2-BCNU (SOWZ2 cultured in BCNU) were applied to validate the roles of LINC00883 in the regulation of multidrug resistance. LINC00883 knockdown suppressed the viability of SWOZ1, SWOZ2, and SWOZ2-BCNU cells.ConclusionIn conclusion, LINC00883 knockdown reduces drug resistance in glioma. Hence, our study provides a future strategy to prevent drug resistance-induced therapeutic failure in glioma.

Although 21 pancreatic cancer susceptibility loci have been identified in individuals of European ancestry through genome-wide association studies (GWASs), much of the heritability of pancreatic cancer risk remains unidentified. A recessive genetic model could be a powerful tool for identifying additional risk variants. To discover recessively inherited pancreatic cancer risk loci, we performed a re-analysis of the largest pancreatic cancer GWAS, the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including 8,769 cases and 7,055 controls of European ancestry. Six single nucleotide polymorphisms (SNPs) showed associations with pancreatic cancer risk according to a recessive model of inheritance. We replicated these variants in 3,212 cases and 3,470 controls collected from the PANcreatic Disease ReseArch (PANDoRA) consortium. The results of the meta-analyses confirmed that rs4626538 (7q32.2), rs7008921 (8p23.2) and rs147904962 (17q21.31) showed specific recessive effects (p10−3), although none of the six SNPs reached the conventional threshold for genome-wide significance (p < 5×10−8). Additional bioinformatic analysis explored the functional annotations of the SNPs and indicated a possible relationship between rs36018702 and expression of the BCL2L11 and BUB1 genes, which are known to be involved in pancreatic biology. Our findings, while not conclusive, indicate the importance of considering non-additive genetic models when performing GWAS analysis. The SNPs associated with pancreatic cancer in this study could be used for further meta-analysis for recessive association of SNPs and pancreatic cancer risk and might be a useful addiction to improve the performance of polygenic risk scores.

BackgroundThe landscape of intratumor heterogeneity (ITH) is present from the tumor evolution. ITH is a promising clinical indicator, but the association between ITH and prognosis remains controversial. Therefore, a meta-analysis was performed to explore whether ITH can serve as a valuable prognostic indicator in solid tumors.MethodsAll included studies were from PubMed, Embase, Cochrane, and Web of Science databases up to October 10, 2020. Studies based on ITH with available prognostic information were included. Three researchers independently completed study selection and data extraction following PRISMA guidelines. The random-effect model was used for synthesis. Hazard ratio (HR) and 95% confidence intervals (CI) were used with the endpoint defined by overall survival (OS), disease-specific survival (DFS), and progression-free survival (PFS).ResultsA total of 9,804 solid tumor patients from 21 studies were included. Analysis of specific cancers in the TCGA database showed similar results based on different ITH assessment methods, which provided the logical support for data consolidation. Available evidence revealed a negative relationship between ITH and prognosis for a specific cancer (such as lung cancer). However, the OS results from 14 tumor types showed that high ITH associated with shorter survival time [HR 1.65 (95% CI, 1.42–1.91)]. PFS and DFS analyses showed similar results [HR 1.89 (95% CI, 1.41–2.54) and HR 1.87 (95% CI, 1.15–3.04)] in general. The status of tumor metastasis and sampling models were not the confounding factors.ConclusionsHigh ITH is associated with worse prognosis in many solid tumors in general although this association was absent for some cancers. ITH is expected to be a promising clinical prognostic factor for the improvement of assessment, treatment, and surveillance strategy.

Recent developments in prostate-specific membrane antigen (PSMA) targeted diagnostic imaging and therapeutics (theranostics) promise to advance the management of primary, biochemically recurrent, and metastatic prostate cancer. In order to maximize the clinical impact of PSMA-targeted theranostics, a coordinated approach between the clinical stakeholders involved in prostate cancer management is required. Here, we present a vision for multidisciplinary use of PSMA theranostics from the viewpoints of nuclear radiology, medical oncology, urology, and radiation oncology. We review the currently available and forthcoming PSMA-based imaging and therapeutics and examine current and potential impacts on prostate cancer management from early localized disease to advanced treatment-refractory disease. Finally, we highlight the clinical and research opportunities related to PSMA-targeted theranostics and describe the importance of multidisciplinary collaboration in this space.

BackgroundPancreatic cancer (PC) has a dismal prognosis due to its insidious early symptoms and poor early detection rate. Exosomes can be released by various cell types and tend to be a potential novel biomarker for PC detection. In this study, we explored the proteomic profiles of plasma exosomes collected from patients with PC at different stages and other pancreatic diseases.MethodsPlasma samples were collected from six groups of patients, including PC at stage I/II, PC at stage III/IV, well-differentiated pancreatic neuroendocrine tumor (P-NET), pancreatic cystic lesions (PCLs), chronic pancreatitis (CP), and healthy controls (HCs). Plasma-derived exosomes were isolated by ultracentrifugation and identified routinely. Isobaric tags for relative and absolute quantification (iTRAQ) based proteomic analysis along with bioinformatic analysis were performed to elucidate the biological functions of proteins. The expression of exosomal ALIX was further confirmed by enzyme-linked immunosorbent assay in a larger cohort of patients. Furthermore, receiver operating characteristic curve analysis was applied to evaluate the potential of ALIX as a novel diagnostic biomarker.ResultsThe proteomic profile revealed a total of 623 proteins expressed among the six groups, and 16 proteins with differential degrees of abundance were found in PC vs. other pancreatic diseases (including P-NET, PCLs, and CP). Based on the results of proteomic and bioinformatic analyses, exosomal ALIX was subsequently selected as a novel biomarker for PC detection and validated in another clinical cohort. We noticed that ALIX expression was elevated in PC patients compared with patients with other pancreatic diseases or HC, and it was also closely associated with TNM stage and distant metastasis. Interestingly, the combination of exosomal ALIX and serum CA199 has greater values in differentiating both early vs. late PC (AUC value 0.872) and PC vs. other pancreatic diseases (AUC value 0.910) than either ALIX or CA199 alone.ConclusionIn summary, our study demonstrated that based on proteomic profiling, proteins isolated from the plasma-derived exosomes may function as ideal non-invasive biomarkers for the clinical diagnosis of PC. Importantly, exosomal ALIX combined with CA199 has great potentials in detection of PC, especially in distinguishing PC patients at early stages from advanced stages.

ObjectivesTo develop a radiomics signature for predicting surgical portal vein-superior mesenteric vein (PV-SMV) in patients with pancreatic ductal adenocarcinoma (PDAC) and measure the effect of providing the predictions of radiomics signature to radiologists with different diagnostic experiences during imaging interpretation.MethodsBetween February 2008 and June 2020, 146 patients with PDAC in pancreatic head or uncinate process from two institutions were retrospectively included and randomly split into a training (n = 88) and a validation (n =58) cohort. Intraoperative vascular exploration findings were used to identify surgical PV-SMV invasion. Radiomics features were extracted from the portal venous phase CT images. Radiomics signature was built with a linear elastic-net regression model. Area under receiver operating characteristic curve (AUC) of the radiomics signature was calculated. A senior and a junior radiologist independently review CT scans and made the diagnosis for PV-SMV invasion both with and without radiomics score (Radscore) assistance. A 2-sided Pearson’s chi-squared test was conducted to evaluate whether there was a difference in sensitivity, specificity, and accuracy between the radiomics signature and the unassisted radiologists. To assess the incremental value of providing Radscore predictions to the radiologists, we compared the performance between unassisted evaluation and Radscore-assisted evaluation by using the McNemar test.ResultsNumbers of patients identified as presence of surgical PV-SMV invasion were 33 (37.5%) and 19 (32.8%) in the training and validation cohort, respectively. The radiomics signature achieved an AUC of 0.848 (95% confidence interval, 0.724–0.971) in the validation cohort and had a comparable sensitivity, specificity, and accuracy as the senior radiologist in predicting PV-SMV invasion (all p-values > 0.05). Providing predictions of radiomics signature increased both radiologists’ sensitivity in identifying PV-SMV invasion, while only the increase of the junior radiologist was significant (63.2 vs 89.5%, p-value = 0.025) instead of the senior radiologist (73.7 vs 89.5%, p-value = 0.08). Both radiologists’ accuracy had no significant increase when provided radiomics signature assistance (both p-values > 0.05).ConclusionsThe radiomics signature can predict surgical PV-SMV invasion in patients with PDAC and may have incremental value to the diagnostic performance of radiologists during imaging interpretation.

ObjectivesTo develop and validate a deep learning-based overall survival (OS) prediction model in patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) plus sorafenib.MethodsThis retrospective multicenter study consisted of 201 patients with treatment-naïve, unresectable HCC who were treated with TACE plus sorafenib. Data from 120 patients were used as the training set for model development. A deep learning signature was constructed using the deep image features from preoperative contrast-enhanced computed tomography images. An integrated nomogram was built using Cox regression by combining the deep learning signature and clinical features. The deep learning signature and nomograms were also externally validated in an independent validation set of 81 patients. C-index was used to evaluate the performance of OS prediction.ResultsThe median OS of the entire set was 19.2 months and no significant difference was found between the training and validation cohort (18.6 months vs. 19.5 months, P = 0.45). The deep learning signature achieved good prediction performance with a C-index of 0.717 in the training set and 0.714 in the validation set. The integrated nomogram showed significantly better prediction performance than the clinical nomogram in the training set (0.739 vs. 0.664, P = 0.002) and validation set (0.730 vs. 0.679, P = 0.023).ConclusionThe deep learning signature provided significant added value to clinical features in the development of an integrated nomogram which may act as a potential tool for individual prognosis prediction and identifying HCC patients who may benefit from the combination therapy of TACE plus sorafenib.

Objectives: To establish a radiomic algorithm based on grayscale ultrasound images and to make preoperative predictions of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients.Methods: In this retrospective study, 322 cases of histopathologically confirmed HCC lesions were included. The classifications based on preoperative grayscale ultrasound images were performed in two stages: (1) classifier #1, MVI-negative and MVI-positive cases; (2) classifier #2, MVI-positive cases were further classified as M1 or M2 cases. The gross-tumoral region (GTR) and peri-tumoral region (PTR) signatures were combined to generate gross- and peri-tumoral region (GPTR) radiomic signatures. The optimal radiomic signatures were further incorporated with vital clinical information. Multivariable logistic regression was used to build radiomic models.Results: Finally, 1,595 radiomic features were extracted from each HCC lesion. At the classifier #1 stage, the radiomic signatures based on features of GTR, PTR, and GPTR showed area under the curve (AUC) values of 0.708 (95% CI, 0.603–0.812), 0.710 (95% CI, 0.609–0.811), and 0.726 (95% CI, 0.625–0.827), respectively. Upon incorporation of vital clinical information, the AUC of the GPTR radiomic algorithm was 0.744 (95% CI, 0.646–0.841). At the classifier #2 stage, the AUC of the GTR radiomic signature was 0.806 (95% CI, 0.667–0.944).Conclusions: Our radiomic algorithm based on grayscale ultrasound images has potential value to facilitate preoperative prediction of MVI in HCC patients. The GTR radiomic signature may be helpful for further discriminating between M1 and M2 levels among MVI-positive patients.

Metabolic reprogramming is prevalent in cancer, largely due to its altered chemical environments such as the distinct intracellular concentrations of O2, H2O2 and H+, compared to those in normal tissue cells. The reprogrammed metabolisms are believed to play essential roles in cancer formation and progression. However, it is highly challenging to elucidate how individual normal metabolisms are altered in a cancer-promoting environment; hence for many metabolisms, our knowledge about how they are changed is limited. We present a novel method, CaMeRe (CAncer MEtabolic REprogramming), for identifying metabolic pathways in cancer tissues. Based on the specified starting and ending compounds, along with gene expression data of given cancer tissue samples, CaMeRe identifies metabolic pathways connecting the two compounds via collection of compatible enzymes, which are most consistent with the provided gene-expression data. In addition, cancer-specific knowledge, such as the expression level of bottleneck enzymes in the pathways, is incorporated into the search process, to enable accurate inference of cancer-specific metabolic pathways. We have applied this tool to predict the altered sugar-energy metabolism in cancer, referred to as the Warburg effect, and found the prediction result is highly accurate by checking the appearance and ranking of those key pathways in the results of CaMeRe. Computational evaluation indicates that the tool is fast and capable of handling large metabolic network inference in cancer tissues. Hence, we believe that CaMeRe offers a powerful tool to cancer researchers for their discovery of reprogrammed metabolisms in cancer. The URL of CaMeRe is http://csbl.bmb.uga.edu/CaMeRe/.